01Key Responsibilities
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Solution Architecture and Delivery
Provide SME & architecture guidance to various teams on various Graph-based project
Lead the design of enterprise-grade solutions leveraging Graph Databases, Databricks, and Gen AI.
Drive integration of LLMs/GenAI with graph-powered data and analytics solutions (e.g., RAG, semantic search, enterprise knowledge assistants).
Serve as the technical partner for clients, engaging in architecture discussions, solution reviews, and delivery governance.
Ensure best practices, scalability, and performance across implementations. COE Leadership &
Capability Building
Engage as an SME in our various Graph Data Engineering projects.
Establish and lead the Graph Data Engineering COE, including defining vision, roadmap, and operating model.
Build reusable accelerators, frameworks, and solution blueprints for graph-powered AI solutions.
Mentor and upskill internal teams to strengthen expertise in graph technologies and knowledge engineering.
Evaluate and onboard emerging graph/AI technologies to stay ahead of the curve.
Go-To-Market & Growth Enablement
Partner with sales and presales teams to develop GTM offerings, proposals, and client solutioning.
Engage directly with clients during discovery workshops, RFPs, and strategy sessions.
Represent the COE in industry forums, thought leadership content, and strategic alliances with partners (e.g., Neo4j, and various cloud providers).
Drive pipeline growth by evangelizing graph + AI solutions across accounts and industries.
Required Skills and Experience
12 15 years of overall experience in Data Engineering, Advanced Analytics, or AI/ML solutions.
Proven expertise with Graph Databases (Neo4j, AWS Neptune, Stardog, Timbr, etc.) and Knowledge Graphs.
Strong Graph Data modeling skills.
Hands-on experience with Databricks (PySpark, Delta Lake, Data Lakehouse, Unity Catalog) and cloud-native data platforms (Azure/AWS/GCP).
Practical experience in designing and delivering LLM/GenAI-enabled solutions with knowledge graphs and vector search.
Track record in solutioning, presales, and GTM enablement, including RFPs and client engagement.
Demonstrated experience in practice/COE building, capability incubation, and team mentoring.
Excellent communication, storytelling, and client-facing skills.
Good-to-Have Skills
Experience with vector databases (Pinecone, etc.) and NLP & embeddings pipelines.
Knowledge of ontologies, taxonomies, and semantic modeling.
Exposure to building AI-powered knowledge assistants, RAG-based enterprise solutions, or domain-specific knowledge platforms.
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